Improving Automation’s Energy Efficiency with Neuromorphic Sensor Technology

While the term industrial automation typically refers to machines with the ability to perform highly-structured, pre-programmed tasks in place of human labor, the term industrial autonomy describes systems that are capable of adapting independently to diverse circumstances with minimal human intervention. For instance, an autonomous robot might be capable of learning to grip an unfamiliar object or navigate a new space without assistance from a human programmer. Artificial intelligence and machine learning provide the internal processing power necessary to enable this, but powerful external sensors are also needed to help robots and other automated technologies perceive and respond to their environments. That’s why technologies such as “sensor fusion,” which grants a single sensor the ability to monitor multiple input types, are on the rise. These advanced sensor technologies are made possible by the exponential growth in computing capacity over the past several decades, which allowed more intelligence to be packed into smaller and smaller devices. However, the added processing power comes at a cost—namely, an increase in energy consumption.